In the modern world, goods or services may be offered through or supported by a telecommunications-based network of call centers that can receive and handle calls from various customers. Such call centers often comprise a combination of human (e.g., customer service representatives) and machine resources that are intended to serve and be responsive to the needs or desires of the customers. Typically, the customer service representatives have varying levels of expertise on particular products and/or services, interpersonal skills, company policies, or any of a number of other areas. Additionally, the customer service representative typically must use a wide array of software applications and programs to access pertinent data. An important objective of a call center network is to provide each customer who calls in with the highest quality of service within the shortest amount of time by the most qualified customer service representative available who has at his or her disposal the appropriate information for a particular customer call.
An incoming call can be received initially by any one of the agents or customer service representatives staffed at the call centers. These customer service representatives, however, might not be able to adequately and/or efficiently handle the needs of the caller. For example, the customer service representatives may not have the skill set, training, understanding of the goods/services, or understanding of the customer service representative user interface to perform the needed tasks accurately and efficiently. In some cases, the customer service representative might need to transfer the caller to a second customer service representative who can properly handle the requests of the caller. At a minimum, the transfer requires an incoming line supporting the call into the receiving call center, an outgoing line from the first customer service representative, and an incoming line into the second customer service representative or call center to which the call was transferred. Transferring a call also might add to the total length of the call for the caller, which could be undesirable. In other cases, if the customer service representative does not transfer the caller, the customer service representative might spend an excessive amount of time to address the issue of the caller. This time may be spent by the customer service representative maneuvering through the multiple screens and programs of the customer service representative user interface to locate the proper information for the caller.
Consequently, in order to provide quality service to customers, it is important to have a customer service representative who is knowledgeable of the goods and services supported by the call center and who can access relevant information with the customer service representative user interface quickly and efficiently. In some instances, it is also important for the customer service representative to recommend promotions or products that may be of interest to the particular caller. The ability to efficiently recommend these promotions or products may require additional training or supervision. Ultimately, in order for a customer service representative to be proficient, the customer service representative typically must be trained and supervised by a supervisor or manager during customer calls. In some cases, a supervisor may “listen in” to the calls to aid in the training. Such training and supervision requires resources and expenses.
Speech recognition systems have previously been developed to process and recognize human speech, and may also take action or carry out further processes. Developments in speech recognition technologies support “natural language” type interactions between automated systems and users. A natural language interaction allows a person to speak naturally. Voice recognition systems can react responsively to a spoken request. Speech recognition technologies typically have been implemented with customer call centers in the area of automatic call routing (“ACR”). A goal of an ACR application is to replace the customer service representative or to lessen the role of a customer service representative during a call. An ACR application typically requires the caller to speak one of a finite set of answers in response to automated questions. The ACR application then attempts to route the caller to an appropriate agent or destination for servicing the caller's request.
ACR systems, however, may not accurately route calls to the proper customer service representatives if the speech recognition system partially understands or misunderstands the caller's intent. Additionally, callers typically prefer to speak directly with a human customer service representative when initiating a call with a call center instead of with an ACR application. As discussed above, even if the caller engages a customer service representative, that particular customer service representative may not have the proper training or skills to adequately address the caller's issue.